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yoni13
2025-01-13 01:38:14 +08:00
parent 68fccad462
commit 1775397a84
5 changed files with 32 additions and 41 deletions
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docs/docs/features/ml-hardware-acceleration.md
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@@ -10,9 +10,9 @@ You do not need to redo any machine learning jobs after enabling hardware accele
## Supported Backends
- ARM NN (Mali)
- RKNN (Rockchip)
- CUDA (NVIDIA GPUs with [compute capability](https://developer.nvidia.com/cuda-gpus) 5.2 or higher)
- OpenVINO (Intel discrete GPUs such as Iris Xe and Arc)
- RKNN (Rockchip)
## Limitations
@@ -35,15 +35,6 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- The `hwaccel.ml.yml` file assumes an additional file `/lib/firmware/mali_csffw.bin`, so update accordingly if your device's driver does not require this file
- Optional: Configure your `.env` file, see [environment variables](/docs/install/environment-variables) for ARM NN specific settings
#### RKNN
- You must have a supported Rockchip SoC, only RK3566 and RK3588 are supported at this moment.
- Make sure you have the appropriate linux kernel driver installed
- This is usually pre-installed on the device vendor's Linux images
- RKNPU driver V0.9.8 or later must be available in the host server
- You may confirm this by running `cat /sys/kernel/debug/rknpu/version` to check the version
- Optional: Configure your `.env` file, see [environment variables](/docs/install/environment-variables) for RKNN specific settings
#### CUDA
- The GPU must have compute capability 5.2 or greater.
@@ -56,6 +47,14 @@ You do not need to redo any machine learning jobs after enabling hardware accele
- The server must have a discrete GPU, i.e. Iris Xe or Arc. Expect issues when attempting to use integrated graphics.
- Ensure the server's kernel version is new enough to use the device for hardware accceleration.
#### RKNN
- You must have a supported Rockchip SoC, only RK3566 and RK3588 are supported at this moment.
- Make sure you have the appropriate linux kernel driver installed
- This is usually pre-installed on the device vendor's Linux images
- RKNPU driver V0.9.8 or later must be available in the host server
- You may confirm this by running `cat /sys/kernel/debug/rknpu/version` to check the version
- Optional: Configure your `.env` file, see [environment variables](/docs/install/environment-variables) for RKNN specific settings
## Setup
1. If you do not already have it, download the latest [`hwaccel.ml.yml`][hw-file] file and ensure it's in the same folder as the `docker-compose.yml`.